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concrete/compiler/lib/Dialect/RT/Analysis/LowerDataflowTasksToRT.cpp

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24 KiB
C++

// Part of the Concrete Compiler Project, under the BSD3 License with Zama
// Exceptions. See
// https://github.com/zama-ai/concrete-compiler-internal/blob/main/LICENSE.txt
// for license information.
#include <iostream>
#include <concretelang/Conversion/Tools.h>
#include <concretelang/Conversion/Utils/GenericOpTypeConversionPattern.h>
#include <concretelang/Dialect/Concrete/IR/ConcreteDialect.h>
#include <concretelang/Dialect/Concrete/IR/ConcreteOps.h>
#include <concretelang/Dialect/Concrete/IR/ConcreteTypes.h>
#include <concretelang/Dialect/FHE/IR/FHEDialect.h>
#include <concretelang/Dialect/FHE/IR/FHEOps.h>
#include <concretelang/Dialect/FHE/IR/FHETypes.h>
#include <concretelang/Dialect/RT/Analysis/Autopar.h>
#include <concretelang/Dialect/RT/IR/RTDialect.h>
#include <concretelang/Dialect/RT/IR/RTOps.h>
#include <concretelang/Dialect/RT/IR/RTTypes.h>
#include <concretelang/Runtime/DFRuntime.hpp>
#include <concretelang/Support/math.h>
#include <llvm/IR/Instructions.h>
#include <mlir/Analysis/DataFlowAnalysis.h>
#include <mlir/Conversion/LLVMCommon/ConversionTarget.h>
#include <mlir/Conversion/LLVMCommon/Pattern.h>
#include <mlir/Conversion/LLVMCommon/VectorPattern.h>
#include <mlir/Dialect/Affine/Utils.h>
#include <mlir/Dialect/Arithmetic/IR/Arithmetic.h>
#include <mlir/Dialect/Bufferization/Transforms/Passes.h>
#include <mlir/Dialect/ControlFlow/IR/ControlFlowOps.h>
#include <mlir/Dialect/Func/IR/FuncOps.h>
#include <mlir/Dialect/Func/Transforms/FuncConversions.h>
#include <mlir/Dialect/LLVMIR/FunctionCallUtils.h>
#include <mlir/Dialect/LLVMIR/LLVMDialect.h>
#include <mlir/Dialect/MemRef/IR/MemRef.h>
#include <mlir/IR/Attributes.h>
#include <mlir/IR/BlockAndValueMapping.h>
#include <mlir/IR/Builders.h>
#include <mlir/IR/BuiltinAttributes.h>
#include <mlir/IR/BuiltinOps.h>
#include <mlir/IR/SymbolTable.h>
#include <mlir/Interfaces/ViewLikeInterface.h>
#include <mlir/Pass/PassManager.h>
#include <mlir/Support/LLVM.h>
#include <mlir/Support/LogicalResult.h>
#include <mlir/Transforms/DialectConversion.h>
#include <mlir/Transforms/Passes.h>
#include <mlir/Transforms/RegionUtils.h>
#define GEN_PASS_CLASSES
#include <concretelang/Dialect/RT/Analysis/Autopar.h.inc>
namespace mlir {
namespace concretelang {
namespace {
static func::FuncOp outlineWorkFunction(RT::DataflowTaskOp DFTOp,
StringRef workFunctionName) {
Location loc = DFTOp.getLoc();
OpBuilder builder(DFTOp.getContext());
Region &DFTOpBody = DFTOp.body();
OpBuilder::InsertionGuard guard(builder);
// Instead of outlining with the same operands/results, we pass all
// results as operands as well. For now we preserve the results'
// types, which will be changed to use an indirection when lowering.
SmallVector<Type, 4> operandTypes;
operandTypes.reserve(DFTOp.getNumOperands() + DFTOp.getNumResults());
for (Value res : DFTOp.getResults())
operandTypes.push_back(RT::PointerType::get(res.getType()));
for (Value operand : DFTOp.getOperands())
operandTypes.push_back(RT::PointerType::get(operand.getType()));
FunctionType type = FunctionType::get(DFTOp.getContext(), operandTypes, {});
auto outlinedFunc = builder.create<func::FuncOp>(loc, workFunctionName, type);
outlinedFunc->setAttr("_dfr_work_function_attribute", builder.getUnitAttr());
Region &outlinedFuncBody = outlinedFunc.getBody();
Block *outlinedEntryBlock = new Block;
SmallVector<Location> locations(type.getInputs().size(), loc);
outlinedEntryBlock->addArguments(type.getInputs(), locations);
outlinedFuncBody.push_back(outlinedEntryBlock);
BlockAndValueMapping map;
int input_offset = DFTOp.getNumResults();
Block &entryBlock = outlinedFuncBody.front();
builder.setInsertionPointToStart(&entryBlock);
for (auto operand : llvm::enumerate(DFTOp.getOperands())) {
// Add deref of arguments and remap to operands in the body
auto derefdop =
builder.create<RT::DerefWorkFunctionArgumentPtrPlaceholderOp>(
DFTOp.getLoc(), operand.value().getType(),
entryBlock.getArgument(operand.index() + input_offset));
map.map(operand.value(), derefdop->getResult(0));
}
DFTOpBody.cloneInto(&outlinedFuncBody, map);
Block &DFTOpEntry = DFTOpBody.front();
Block *clonedDFTOpEntry = map.lookup(&DFTOpEntry);
builder.setInsertionPointToEnd(&entryBlock);
builder.create<cf::BranchOp>(loc, clonedDFTOpEntry);
// WorkFunctionReturnOp ties return to the corresponding argument.
// This is lowered to a copy/deref for shared memory and pointers,
// and handled in the serializer for distributed memory.
outlinedFunc.walk([&](RT::DataflowYieldOp op) {
OpBuilder replacer(op);
for (auto ret : llvm::enumerate(op.getOperands()))
replacer.create<RT::WorkFunctionReturnOp>(
op.getLoc(), ret.value(), outlinedFunc.getArgument(ret.index()));
replacer.create<func::ReturnOp>(op.getLoc());
op.erase();
});
return outlinedFunc;
}
static void replaceAllUsesInDFTsInRegionWith(Value orig, Value replacement,
Region &region) {
for (auto &use : llvm::make_early_inc_range(orig.getUses())) {
if ((isa<RT::DataflowTaskOp>(use.getOwner()) ||
isa<RT::DeallocateFutureOp>(use.getOwner())) &&
region.isAncestor(use.getOwner()->getParentRegion()))
use.set(replacement);
}
}
static mlir::Type stripType(mlir::Type type) {
if (type.isa<RT::FutureType>())
return stripType(type.dyn_cast<RT::FutureType>().getElementType());
if (type.isa<RT::PointerType>())
return stripType(type.dyn_cast<RT::PointerType>().getElementType());
return type;
}
// TODO: Fix type sizes. For now we're using some default values.
static std::pair<Value, Value>
getTaskArgumentSizeAndType(Value val, Location loc, OpBuilder builder) {
DataLayout dataLayout = DataLayout::closest(val.getDefiningOp());
Type type = stripType(val.getType());
// In the case of memref, we need to determine how much space
// (conservatively) we need to store the memref itself. Overshooting
// by a few bytes should not be an issue, so the main thing is to
// properly account for the rank.
if (type.isa<mlir::MemRefType>()) {
// Space for the allocated and aligned pointers, and offset plus
// rank * sizes and strides
size_t element_size;
unsigned rank = type.dyn_cast<mlir::MemRefType>().getRank();
Type elementType = type.dyn_cast<mlir::MemRefType>().getElementType();
element_size = dataLayout.getTypeSize(elementType);
size_t size = 24 + 16 * rank;
Value typeSize =
builder.create<arith::ConstantOp>(loc, builder.getI64IntegerAttr(size));
// Assume here that the base type is a simple scalar-type or at
// least its size can be determined.
// size_t elementAttr = dataLayout.getTypeSize(elementType);
// Make room for a byte to store the type of this argument/output
// elementAttr <<= 8;
// elementAttr |= _DFR_TASK_ARG_MEMREF;
uint64_t elementAttr = 0;
elementAttr =
dfr::_dfr_set_arg_type(elementAttr, dfr::_DFR_TASK_ARG_MEMREF);
elementAttr = dfr::_dfr_set_memref_element_size(elementAttr, element_size);
Value arg_type = builder.create<arith::ConstantOp>(
loc, builder.getI64IntegerAttr(elementAttr));
return std::pair<mlir::Value, mlir::Value>(typeSize, arg_type);
}
if (type.isa<mlir::concretelang::Concrete::ContextType>()) {
Value arg_type = builder.create<arith::ConstantOp>(
loc, builder.getI64IntegerAttr(dfr::_DFR_TASK_ARG_CONTEXT));
Value typeSize =
builder.create<arith::ConstantOp>(loc, builder.getI64IntegerAttr(8));
return std::pair<mlir::Value, mlir::Value>(typeSize, arg_type);
}
Value arg_type = builder.create<arith::ConstantOp>(
loc, builder.getI64IntegerAttr(dfr::_DFR_TASK_ARG_BASE));
Value typeSize = builder.create<arith::ConstantOp>(
loc, builder.getI64IntegerAttr(dataLayout.getTypeSize(type)));
return std::pair<mlir::Value, mlir::Value>(typeSize, arg_type);
}
static void lowerDataflowTaskOp(RT::DataflowTaskOp DFTOp,
func::FuncOp workFunction) {
Region &opBody = DFTOp->getParentOfType<func::FuncOp>().getBody();
OpBuilder builder(DFTOp);
// First identify DFT operands that are not futures and are not
// defined by another DFT. These need to be made into futures and
// propagated to all other DFTs. We can allow PRE to eliminate the
// previous definitions if there are no non-future type uses.
for (Value val : DFTOp.getOperands()) {
if (!val.getType().isa<RT::FutureType>()) {
OpBuilder::InsertionGuard guard(builder);
Type futType = RT::FutureType::get(val.getType());
// Find out if this value is needed in any other task
SmallVector<Operation *, 2> taskOps;
for (auto &use : val.getUses())
if (isa<RT::DataflowTaskOp>(use.getOwner()))
taskOps.push_back(use.getOwner());
Operation *first = DFTOp;
for (auto op : taskOps)
if (first->getBlock() == op->getBlock() && op->isBeforeInBlock(first))
first = op;
builder.setInsertionPoint(first);
auto mrf = builder.create<RT::MakeReadyFutureOp>(
val.getLoc(), futType, val,
builder.create<arith::ConstantOp>(val.getLoc(),
builder.getI64IntegerAttr(0)));
replaceAllUsesInDFTsInRegionWith(val, mrf, opBody);
}
}
// Second generate a CreateAsyncTaskOp that will replace the
// DataflowTaskOp. This also includes the necessary handling of
// operands and results (conversion to/from futures and propagation).
SmallVector<Value, 4> catOperands;
int size = 3 + DFTOp.getNumResults() + DFTOp.getNumOperands();
catOperands.reserve(size);
auto fnptr = builder.create<mlir::func::ConstantOp>(
DFTOp.getLoc(), workFunction.getFunctionType(),
SymbolRefAttr::get(builder.getContext(), workFunction.getName()));
auto numIns = builder.create<arith::ConstantOp>(
DFTOp.getLoc(), builder.getI64IntegerAttr(DFTOp.getNumOperands()));
auto numOuts = builder.create<arith::ConstantOp>(
DFTOp.getLoc(), builder.getI64IntegerAttr(DFTOp.getNumResults()));
catOperands.push_back(fnptr.getResult());
catOperands.push_back(numIns.getResult());
catOperands.push_back(numOuts.getResult());
// We need to adjust the results for the CreateAsyncTaskOp which
// are the work function's returns through pointers passed as
// parameters. As this is not supported within MLIR - and mostly
// unsupported even in the LLVMIR Dialect - this needs to use two
// placeholders for each output, before and after the
// CreateAsyncTaskOp.
BlockAndValueMapping map;
for (auto result : DFTOp.getResults()) {
Type futType = RT::PointerType::get(RT::FutureType::get(result.getType()));
auto brpp = builder.create<RT::BuildReturnPtrPlaceholderOp>(DFTOp.getLoc(),
futType);
map.map(result, brpp->getResult(0));
catOperands.push_back(brpp->getResult(0));
}
for (auto operand : DFTOp.getOperands()) {
catOperands.push_back(operand);
}
builder.create<RT::CreateAsyncTaskOp>(
DFTOp.getLoc(),
SymbolRefAttr::get(builder.getContext(), workFunction.getName()),
catOperands);
// Third identify results of this DFT that are not used *only* in
// other DFTs as those will need to be waited on explicitly.
// We also create the DerefReturnPtrPlaceholderOp after the
// CreateAsyncTaskOp. These also need propagating.
for (auto result : DFTOp.getResults()) {
Type futType = RT::FutureType::get(result.getType());
Value futptr = map.lookupOrNull(result);
assert(futptr);
auto drpp = builder.create<RT::DerefReturnPtrPlaceholderOp>(
DFTOp.getLoc(), futType, futptr);
replaceAllUsesInDFTsInRegionWith(result, drpp->getResult(0), opBody);
for (auto &use : llvm::make_early_inc_range(result.getUses())) {
if (!isa<RT::DataflowTaskOp>(use.getOwner()) &&
!isa<RT::DeallocateFutureOp>(use.getOwner()) &&
use.getOwner()->getParentOfType<RT::DataflowTaskOp>() == nullptr) {
// Wait for this future before its uses
OpBuilder::InsertionGuard guard(builder);
builder.setInsertionPoint(use.getOwner());
auto af = builder.create<RT::AwaitFutureOp>(
DFTOp.getLoc(), result.getType(), drpp.getResult());
assert(opBody.isAncestor(use.getOwner()->getParentRegion()));
use.set(af->getResult(0));
}
}
// All leftover uses (i.e. those within DFTs should use the future)
replaceAllUsesInRegionWith(result, futptr, opBody);
}
// Finally erase the DFT.
DFTOp.erase();
}
static void registerWorkFunction(mlir::func::FuncOp parentFunc,
mlir::func::FuncOp workFunction) {
OpBuilder builder(parentFunc.getBody());
builder.setInsertionPointToStart(&parentFunc.getBody().front());
auto fnptr = builder.create<mlir::func::ConstantOp>(
parentFunc.getLoc(), workFunction.getFunctionType(),
SymbolRefAttr::get(builder.getContext(), workFunction.getName()));
builder.create<RT::RegisterTaskWorkFunctionOp>(parentFunc.getLoc(),
fnptr.getResult());
}
static func::FuncOp getCalledFunction(CallOpInterface callOp) {
SymbolRefAttr sym = callOp.getCallableForCallee().dyn_cast<SymbolRefAttr>();
if (!sym)
return nullptr;
return dyn_cast_or_null<func::FuncOp>(
SymbolTable::lookupNearestSymbolFrom(callOp, sym));
}
/// For documentation see Autopar.td
struct LowerDataflowTasksPass
: public LowerDataflowTasksBase<LowerDataflowTasksPass> {
void runOnOperation() override {
auto module = getOperation();
SmallVector<func::FuncOp, 4> workFunctions;
SmallVector<func::FuncOp, 1> entryPoints;
module.walk([&](mlir::func::FuncOp func) {
static int wfn_id = 0;
// TODO: For now do not attempt to use nested parallelism.
if (func->getAttr("_dfr_work_function_attribute"))
return;
SymbolTable symbolTable = mlir::SymbolTable::getNearestSymbolTable(func);
SmallVector<std::pair<RT::DataflowTaskOp, func::FuncOp>, 4> outliningMap;
// Outline DataflowTaskOp bodies to work functions
func.walk([&](RT::DataflowTaskOp op) {
auto workFunctionName =
Twine("_dfr_DFT_work_function__") +
Twine(op->getParentOfType<func::FuncOp>().getName()) +
Twine(wfn_id++);
func::FuncOp outlinedFunc =
outlineWorkFunction(op, workFunctionName.str());
outliningMap.push_back(
std::pair<RT::DataflowTaskOp, func::FuncOp>(op, outlinedFunc));
symbolTable.insert(outlinedFunc);
workFunctions.push_back(outlinedFunc);
return WalkResult::advance();
});
// Lower the DF task ops to RT dialect ops.
for (auto mapping : outliningMap)
lowerDataflowTaskOp(mapping.first, mapping.second);
// Gather all entry points (assuming no recursive calls to entry points)
// Main is always an entry-point - otherwise check if this
// function is called within the module. TODO: we assume no
// recursion.
if (func.getName() == "main")
entryPoints.push_back(func);
else {
bool found = false;
module.walk([&](mlir::func::CallOp op) {
if (getCalledFunction(op) == func)
found = true;
});
if (!found)
entryPoints.push_back(func);
}
});
for (auto entryPoint : entryPoints) {
// If this is a JIT invocation and we're not on the root node,
// we do not need to do any computation, only register all work
// functions with the runtime system
if (!workFunctions.empty()) {
if (!dfr::_dfr_is_root_node()) {
entryPoint.eraseBody();
Block *b = new Block;
FunctionType funTy = entryPoint.getFunctionType();
SmallVector<Location> locations(funTy.getInputs().size(),
entryPoint.getLoc());
b->addArguments(funTy.getInputs(), locations);
entryPoint.getBody().push_front(b);
for (int i = funTy.getNumInputs() - 1; i >= 0; --i)
entryPoint.eraseArgument(i);
for (int i = funTy.getNumResults() - 1; i >= 0; --i)
entryPoint.eraseResult(i);
OpBuilder builder(entryPoint.getBody());
builder.setInsertionPointToEnd(&entryPoint.getBody().front());
builder.create<mlir::func::ReturnOp>(entryPoint.getLoc());
}
}
// Generate code to register all work-functions with the
// runtime.
for (auto wf : workFunctions)
registerWorkFunction(entryPoint, wf);
}
}
LowerDataflowTasksPass(bool debug) : debug(debug){};
protected:
bool debug;
};
} // end anonymous namespace
std::unique_ptr<mlir::Pass> createLowerDataflowTasksPass(bool debug) {
return std::make_unique<LowerDataflowTasksPass>(debug);
}
namespace {
// For documentation see Autopar.td
struct StartStopPass : public StartStopBase<StartStopPass> {
void runOnOperation() override {
auto module = getOperation();
int useDFR = 0;
SmallVector<func::FuncOp, 1> entryPoints;
module.walk([&](mlir::func::FuncOp func) {
// Do not add start/stop to work functions - but if any are
// present, then we need to activate the runtime
if (func->getAttr("_dfr_work_function_attribute")) {
useDFR = 1;
} else {
// Main is always an entry-point - otherwise check if this
// function is called within the module. TODO: we assume no
// recursion.
if (func.getName() == "main")
entryPoints.push_back(func);
else {
bool found = false;
module.walk([&](mlir::func::CallOp op) {
if (getCalledFunction(op) == func)
found = true;
});
if (!found)
entryPoints.push_back(func);
}
}
});
for (auto entryPoint : entryPoints) {
// Issue _dfr_start/stop calls for this function
OpBuilder builder(entryPoint.getBody());
builder.setInsertionPointToStart(&entryPoint.getBody().front());
Value useDFRVal = builder.create<arith::ConstantOp>(
entryPoint.getLoc(), builder.getI64IntegerAttr(useDFR));
// Check if this entry point uses a context
Value ctx = nullptr;
if (dfr::_dfr_is_root_node())
for (auto arg : llvm::enumerate(entryPoint.getArguments()))
if (arg.value()
.getType()
.isa<mlir::concretelang::Concrete::ContextType>()) {
ctx = arg.value();
break;
}
if (!ctx)
ctx = builder.create<arith::ConstantOp>(entryPoint.getLoc(),
builder.getI64IntegerAttr(0));
auto startFunTy = mlir::FunctionType::get(
entryPoint->getContext(), {useDFRVal.getType(), ctx.getType()}, {});
(void)insertForwardDeclaration(entryPoint, builder, "_dfr_start",
startFunTy);
builder.create<mlir::func::CallOp>(entryPoint.getLoc(), "_dfr_start",
mlir::TypeRange(),
mlir::ValueRange({useDFRVal, ctx}));
builder.setInsertionPoint(entryPoint.getBody().back().getTerminator());
auto stopFunTy = mlir::FunctionType::get(entryPoint->getContext(),
{useDFRVal.getType()}, {});
(void)insertForwardDeclaration(entryPoint, builder, "_dfr_stop",
stopFunTy);
builder.create<mlir::func::CallOp>(entryPoint.getLoc(), "_dfr_stop",
mlir::TypeRange(), useDFRVal);
}
}
StartStopPass(bool debug) : debug(debug){};
protected:
bool debug;
};
} // namespace
std::unique_ptr<mlir::Pass> createStartStopPass(bool debug) {
return std::make_unique<StartStopPass>(debug);
}
namespace {
// For documentation see Autopar.td
struct FinalizeTaskCreationPass
: public FinalizeTaskCreationBase<FinalizeTaskCreationPass> {
void runOnOperation() override {
auto module = getOperation();
std::vector<Operation *> ops;
module.walk([&](RT::CreateAsyncTaskOp catOp) {
OpBuilder builder(catOp);
SmallVector<Value, 4> operands;
// Determine if this task needs a runtime context
Value ctx = nullptr;
SymbolRefAttr sym =
catOp->getAttr("workfn").dyn_cast_or_null<SymbolRefAttr>();
assert(sym && "Work function symbol attribute missing.");
func::FuncOp workfn = dyn_cast_or_null<func::FuncOp>(
SymbolTable::lookupNearestSymbolFrom(catOp, sym));
assert(workfn && "Task work function missing.");
if (workfn.getNumArguments() > catOp.getNumOperands() - 3)
ctx = *catOp->getParentOfType<func::FuncOp>().getArguments().rbegin();
else
ctx = builder.create<arith::ConstantOp>(catOp.getLoc(),
builder.getI64IntegerAttr(0));
int index = 0;
for (auto op : catOp.getOperands()) {
operands.push_back(op);
// Add index in second position - in all cases to avoid
// checking if needed. It can be null when not relevant.
if (index == 0)
operands.push_back(ctx);
// First three operands are the function pointer, number inputs
// and number outputs - nothing further to do.
if (++index <= 3)
continue;
auto op_size = getTaskArgumentSizeAndType(op, catOp.getLoc(), builder);
operands.push_back(op_size.first);
operands.push_back(op_size.second);
}
builder.create<RT::CreateAsyncTaskOp>(catOp.getLoc(), sym, operands);
ops.push_back(catOp);
});
for (auto op : ops) {
op->erase();
}
// If we are building a future on a MemRef, we need to flatten it.
// TODO: the performance of shared memory can be improved by
// allowing view-like access instead of cloning, but memory
// deallocation needs to be synchronized appropriately
module.walk([&](RT::MakeReadyFutureOp op) {
OpBuilder builder(op);
Value val = op.getOperand(0);
Value clone = op.getOperand(1);
if (val.getType().isa<mlir::MemRefType>()) {
MemRefType mrType_base = val.getType().dyn_cast<mlir::MemRefType>();
MemRefType mrType = mrType_base;
if (!mrType_base.getLayout().isIdentity()) {
unsigned rank = mrType_base.getRank();
mrType = MemRefType::Builder(mrType_base)
.setShape(mrType_base.getShape())
.setLayout(AffineMapAttr::get(
builder.getMultiDimIdentityMap(rank)));
}
// We need to make a copy of this MemRef to allow deallocation
// based on refcounting
Value newval =
builder.create<mlir::memref::AllocOp>(val.getLoc(), mrType)
.getResult();
builder.create<mlir::memref::CopyOp>(val.getLoc(), val, newval);
clone = builder.create<arith::ConstantOp>(op.getLoc(),
builder.getI64IntegerAttr(1));
op->setOperand(0, newval);
op->setOperand(1, clone);
}
});
}
FinalizeTaskCreationPass(bool debug) : debug(debug){};
protected:
bool debug;
};
} // namespace
std::unique_ptr<mlir::Pass> createFinalizeTaskCreationPass(bool debug) {
return std::make_unique<FinalizeTaskCreationPass>(debug);
}
namespace {
static void getAliasedUses(Value val, DenseSet<OpOperand *> &aliasedUses) {
for (auto &use : val.getUses()) {
aliasedUses.insert(&use);
if (dyn_cast<ViewLikeOpInterface>(use.getOwner()))
getAliasedUses(use.getOwner()->getResult(0), aliasedUses);
}
}
// For documentation see Autopar.td
struct FixupBufferDeallocationPass
: public FixupBufferDeallocationBase<FixupBufferDeallocationPass> {
void runOnOperation() override {
auto module = getOperation();
std::vector<Operation *> ops;
module.walk([&](mlir::memref::DeallocOp op) {
Value alloc = op.getOperand();
DenseSet<OpOperand *> aliasedUses;
getAliasedUses(alloc, aliasedUses);
for (auto use : aliasedUses)
if (isa<RT::WorkFunctionReturnOp, RT::MakeReadyFutureOp>(
use->getOwner())) {
ops.push_back(op);
return;
}
});
for (auto op : ops) {
op->erase();
}
}
FixupBufferDeallocationPass(bool debug) : debug(debug){};
protected:
bool debug;
};
} // end anonymous namespace
std::unique_ptr<mlir::Pass> createFixupBufferDeallocationPass(bool debug) {
return std::make_unique<FixupBufferDeallocationPass>(debug);
}
} // end namespace concretelang
} // end namespace mlir